Predicting QB Success in the NFL

Last year I wrote and submitted a paper for the MIT Sloan Sports Analytics Conference. While my abstract was accepted my paper was not. The title of my paper was Reducing Risk in the NFL Draft: Using Machine Learning Algorithms to Predict Success in the NFL. You can read the full paper here.

In it I describe a decision tree model that predicts a college QBs success in the NFL. To train the model I used over 40 variables including college stats, school competitiveness, combine performance, and text mining of pro scouting reports. Ultimately, the final model used 4 variables: college win %, body mass index (BMI), college games started per season, and age. The final model was 88% accurate in predicting whether a college player would be a success or a bust in the NFL. This model can be used to predict whether the top prospects in this year's draft will be successful in the NFL.